4 days ago
Prague, CzechiaSenior
Responsibilities
- Design, build, and maintain scalable, reliable, and cost-effective AI platform infrastructure in the cloud.
- Collaborate with Research to translate model requirements into scalable production infrastructure.
- Improve data pipelines, feature storage, experiment tracking, and model lifecycle workflows.
- Build tooling for experimentation, benchmarking, and reproducibility.
- Implement monitoring, observability, and reliability improvements across AI services.
- Contribute to architecture discussions and long-term platform strategy.
- Partner with Product, Research, and engineering teams to align platform capabilities with product needs.
- Maintain documentation and support knowledge-sharing across R&D.
Requirements
- 5+ years of experience in product-minded software engineering, ML platform engineering, or infrastructure roles.
- Proven experience delivering ML solutions with measurable business and customer impact.
- Strong programming experience in a language suitable for ML, such as Python.
- Understanding of distributed systems, microservices, and cloud-native architectures.
- Experience with SQL databases, including query optimization, performance tuning, and schema design.
- Experience with ML tooling such as experiment tracking, model registries, and data pipelines.
- Strong problem-solving skills and ability to work in cross-functional R&D environments.
- Understanding of CI/CD, infrastructure-as-code, and observability tooling.
- Ability to communicate internally in English.
- Preferred experience includes training or serving AI/ML models at scale, scalable ETL/ELT pipelines, SQL/NoSQL database architectures, data annotation and dataset management, GPU workloads, batch or stream processing, feature stores, Intelligent Document Processing, and deep neural network architectures.
Benefits
- Work on proprietary T-LLM architectures designed and trained in-house, with high-end GPU and large-memory compute clusters.
- Work on high-scale transaction data and systems used by companies globally, with direct ownership from research through production.
- Access to frontier LLMs and an experiment-driven culture with quarterly recognition for standout research contributions.
- 33 days off including PTO, personal days, a birthday day, and two company wellness days, plus parental leave.
- Prague Karlín workspace with full technical setup and a 200 m² terrace.
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